{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "A module that was compiled using NumPy 1.x cannot be run in\n",
      "NumPy 2.0.0 as it may crash. To support both 1.x and 2.x\n",
      "versions of NumPy, modules must be compiled with NumPy 2.0.\n",
      "Some module may need to rebuild instead e.g. with 'pybind11>=2.12'.\n",
      "\n",
      "If you are a user of the module, the easiest solution will be to\n",
      "downgrade to 'numpy<2' or try to upgrade the affected module.\n",
      "We expect that some modules will need time to support NumPy 2.\n",
      "\n",
      "Traceback (most recent call last):  File \"/root/miniconda3/lib/python3.10/runpy.py\", line 196, in _run_module_as_main\n",
      "    return _run_code(code, main_globals, None,\n",
      "  File \"/root/miniconda3/lib/python3.10/runpy.py\", line 86, in _run_code\n",
      "    exec(code, run_globals)\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/ipykernel_launcher.py\", line 17, in <module>\n",
      "    app.launch_new_instance()\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/traitlets/config/application.py\", line 1075, in launch_instance\n",
      "    app.start()\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/ipykernel/kernelapp.py\", line 701, in start\n",
      "    self.io_loop.start()\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/tornado/platform/asyncio.py\", line 205, in start\n",
      "    self.asyncio_loop.run_forever()\n",
      "  File \"/root/miniconda3/lib/python3.10/asyncio/base_events.py\", line 603, in run_forever\n",
      "    self._run_once()\n",
      "  File \"/root/miniconda3/lib/python3.10/asyncio/base_events.py\", line 1909, in _run_once\n",
      "    handle._run()\n",
      "  File \"/root/miniconda3/lib/python3.10/asyncio/events.py\", line 80, in _run\n",
      "    self._context.run(self._callback, *self._args)\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/ipykernel/kernelbase.py\", line 534, in dispatch_queue\n",
      "    await self.process_one()\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/ipykernel/kernelbase.py\", line 523, in process_one\n",
      "    await dispatch(*args)\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/ipykernel/kernelbase.py\", line 429, in dispatch_shell\n",
      "    await result\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/ipykernel/kernelbase.py\", line 767, in execute_request\n",
      "    reply_content = await reply_content\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/ipykernel/ipkernel.py\", line 429, in do_execute\n",
      "    res = shell.run_cell(\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/ipykernel/zmqshell.py\", line 549, in run_cell\n",
      "    return super().run_cell(*args, **kwargs)\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/IPython/core/interactiveshell.py\", line 3051, in run_cell\n",
      "    result = self._run_cell(\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/IPython/core/interactiveshell.py\", line 3106, in _run_cell\n",
      "    result = runner(coro)\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/IPython/core/async_helpers.py\", line 129, in _pseudo_sync_runner\n",
      "    coro.send(None)\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/IPython/core/interactiveshell.py\", line 3311, in run_cell_async\n",
      "    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/IPython/core/interactiveshell.py\", line 3493, in run_ast_nodes\n",
      "    if await self.run_code(code, result, async_=asy):\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/IPython/core/interactiveshell.py\", line 3553, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"/tmp/ipykernel_3800/3919361102.py\", line 1, in <module>\n",
      "    from gru import Gru\n",
      "  File \"/root/gru/gru.py\", line 1, in <module>\n",
      "    import torch\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/torch/__init__.py\", line 1382, in <module>\n",
      "    from .functional import *  # noqa: F403\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/torch/functional.py\", line 7, in <module>\n",
      "    import torch.nn.functional as F\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/torch/nn/__init__.py\", line 1, in <module>\n",
      "    from .modules import *  # noqa: F403\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/torch/nn/modules/__init__.py\", line 35, in <module>\n",
      "    from .transformer import TransformerEncoder, TransformerDecoder, \\\n",
      "  File \"/root/miniconda3/lib/python3.10/site-packages/torch/nn/modules/transformer.py\", line 20, in <module>\n",
      "    device: torch.device = torch.device(torch._C._get_default_device()),  # torch.device('cpu'),\n",
      "/root/miniconda3/lib/python3.10/site-packages/torch/nn/modules/transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:84.)\n",
      "  device: torch.device = torch.device(torch._C._get_default_device()),  # torch.device('cpu'),\n"
     ]
    }
   ],
   "source": [
    "from gru import Gru\n",
    "from load_data import loaddata, loadradar, normalize, resample\n",
    "from turbine_dataset import TurbineDataset\n",
    "from torch.utils.data import DataLoader\n",
    "from torch.optim import Adam\n",
    "from torch import nn\n",
    "from trainer import Trainer\n",
    "import torch\n",
    "from radar_dataset import RadarDataset\n",
    "import numpy as np\n",
    "from model import Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainrate = 0.8\n",
    "testrate = 0.1\n",
    "seq = 24\n",
    "device = \"cuda\"\n",
    "batch_size = 128\n",
    "hidden_size = 256\n",
    "output_size = 1\n",
    "num_layers = 3\n",
    "epoch = 100\n",
    "target_col = 'RadWdSpd1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/root/gru/load_data.py:20: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  source_df['u'] = np.cos(np.radians(source_df['NacWdDir1'])) * source_df['NacWdSpdFltS']\n",
      "/root/gru/load_data.py:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  source_df['v'] = np.sin(np.radians(source_df['NacWdDir1'])) * source_df['NacWdSpdFltS']\n"
     ]
    }
   ],
   "source": [
    "input_size, df = loadradar()\n",
    "target_idx = len(df.columns) - 1\n",
    "roll_cols=['NacWdSpdFltS', 'CnvW400v', 'u', 'v']\n",
    "\n",
    "lags = 2\n",
    "input_size += lags * len(roll_cols)\n",
    "for col in roll_cols:\n",
    "    for i in range(lags):\n",
    "        df[f'lag{i}' + col] = df[col].shift(i)\n",
    "\n",
    "diff = 2\n",
    "input_size += diff * len(roll_cols)\n",
    "for col in roll_cols:\n",
    "    df['diff0' + col] = df[col].diff()\n",
    "    for i in range(diff - 1):\n",
    "        df[f'diff{i + 1}' + col] = df[f'diff{i}' + col].diff()\n",
    "\n",
    "df = df.fillna(0)\n",
    "df, scaler = normalize(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainset = RadarDataset(df[:int(trainrate * len(df))], seq, device, target_col)\n",
    "valset = RadarDataset(df[int(trainrate * len(df)): -int(len(df) * testrate)], seq, device, target_col)\n",
    "testset = RadarDataset(df[-int(len(df) * testrate):], seq, device, target_col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainloader = DataLoader(trainset, batch_size=batch_size, shuffle=True)\n",
    "valloader = DataLoader(valset, batch_size=batch_size)\n",
    "testloader = DataLoader(testset, batch_size=batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Model(input_size, hidden_size, output_size, num_layers).to(device=device)\n",
    "optimizer = Adam(model.parameters(), lr=0.0001)\n",
    "criterion = nn.HuberLoss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "trainer = Trainer(criterion, optimizer, model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3780/3780 [00:56<00:00, 66.53it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training 0th epoch, train loss is 0.03794729346557269\n",
      "val loss is 0.057410163647371164\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3780/3780 [00:56<00:00, 67.46it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training 1th epoch, train loss is 0.03287261496421206\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3780/3780 [00:54<00:00, 69.35it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training 2th epoch, train loss is 0.031243227969451004\n",
      "val loss is 0.052835368209205424\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3780/3780 [00:53<00:00, 70.16it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training 3th epoch, train loss is 0.029236699124950936\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3780/3780 [00:55<00:00, 67.91it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training 4th epoch, train loss is 0.026721823883178845\n",
      "val loss is 0.0576860646448486\n",
      "early stop 1 / 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3780/3780 [00:55<00:00, 67.95it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training 5th epoch, train loss is 0.023232745673142808\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3780/3780 [00:56<00:00, 66.64it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training 6th epoch, train loss is 0.019321185936683187\n",
      "val loss is 0.06598143732144712\n",
      "early stop 2 / 3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3780/3780 [00:55<00:00, 67.55it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training 7th epoch, train loss is 0.015318848464697126\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 3780/3780 [00:54<00:00, 68.84it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training 8th epoch, train loss is 0.012078422896081098\n",
      "val loss is 0.07302720558309797\n",
      "early stop 3 / 3\n"
     ]
    }
   ],
   "source": [
    "trainer.train(trainloader, valloader, epoch=epoch, valepoch=2)\n",
    "# model.load_state_dict(torch.load(\"model_50.pth\"))\n",
    "# torch.save(model.state_dict(), f\"model_{seq}_{epoch}.pth\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "mean = torch.tensor(scaler.mean_, dtype=torch.float32).to(device)\n",
    "std = torch.tensor(np.sqrt(scaler.var_), dtype=torch.float32).to(device)\n",
    "y_p, y_t = trainer.predict(testloader, mean, std, target_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.1872867136798138\n",
      "0.3348964489222488\n",
      "0.08359818712125133\n"
     ]
    }
   ],
   "source": [
    "mseloss = 0\n",
    "maeloss = 0\n",
    "mapeloss = 0\n",
    "for t, p in zip(y_t, y_p):\n",
    "    mseloss += (t - p) ** 2\n",
    "    maeloss += abs(t - p)\n",
    "    mapeloss += abs(t - p) / abs(t)\n",
    "print(mseloss / len(y_t))\n",
    "print(maeloss / len(y_t))\n",
    "print(mapeloss / len(y_t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "60456\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "# 假设 predictions 和 actual_values 已经定义\n",
    "# predictions 是模型的预测值，actual_values 是真实值\n",
    "\n",
    "actual_values = y_t\n",
    "predictions = y_p\n",
    "print(len(actual_values))\n",
    "length = -1\n",
    "actual_values = actual_values[:length]\n",
    "predictions = predictions[:length]\n",
    "\n",
    "# 创建散点图\n",
    "plt.scatter(actual_values, predictions, color='blue', label='Actual vs Predicted')\n",
    "\n",
    "# 添加标签和标题\n",
    "plt.xlabel('Actual Values')\n",
    "plt.ylabel('Predicted Values')\n",
    "plt.title('Actual vs Predicted Values')\n",
    "\n",
    "# 添加对角线，用于比较完美预测的情况\n",
    "plt.plot([min(actual_values), max(actual_values)], [min(actual_values), max(actual_values)], linestyle='--', color='red', linewidth=2, label='Perfect Prediction')\n",
    "\n",
    "# 显示图例\n",
    "plt.legend()\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f24e0efeec0>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "length = 500\n",
    "start = 3000\n",
    "x = [i for i in range(length)]\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(x, y_p[start: start + length], color=\"red\")\n",
    "plt.plot(x, y_t[start: start + length])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/root/gru/load_data.py:20: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  source_df['u'] = np.cos(np.radians(source_df['NacWdDir1'])) * source_df['NacWdSpdFltS']\n",
      "/root/gru/load_data.py:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  source_df['v'] = np.sin(np.radians(source_df['NacWdDir1'])) * source_df['NacWdSpdFltS']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.7084327   0.05120768  0.2633838  ... -0.64895196 -0.27479147\n",
      "   0.05072979]\n",
      " [-0.70609272  0.05797359  0.2633838  ... -0.62353151 -0.18513647\n",
      "  -0.00967968]\n",
      " [-0.70609272  0.05797359  0.2633838  ... -0.66495185 -0.33696297\n",
      "  -0.06203455]\n",
      " ...\n",
      " [-0.44869558  0.53158702  0.2633838  ... -0.39562123 -0.38457139\n",
      "  -0.18553835]\n",
      " [-0.41593594  0.53158702  0.2633838  ... -0.28580194  0.07128721\n",
      "  -0.1586897 ]\n",
      " [-0.39721615  0.52482111  0.2633838  ... -0.2745456  -0.01289898\n",
      "  -0.56947409]]\n",
      "[0, 55402, 7981, 9486, 12249, 15067, 20070, 24287, 29239, 36796, 41225, 46883, 46466, 44995, 43960, 37429, 26730, 18854, 15351, 12336, 10463, 8632, 7204, 6012, 5051, 4354, 3462, 2779, 2270, 1779, 1461, 1167, 991, 744, 631, 475, 390, 277, 241, 190, 144, 132, 111, 79, 56, 74, 43, 44, 39, 699]\n",
      "604800\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler()\n",
    "input_size, df = loadradar()\n",
    "df['RadWdSpd1'] -= df['NacWdSpdFltS']\n",
    "rdf = scaler.fit_transform(df)\n",
    "print(rdf)\n",
    "y_distr = [0 for _ in range(50)]\n",
    "for i in range(len(rdf)):\n",
    "    y = rdf[i]\n",
    "    for base in range(1, 50):\n",
    "        if y[-1] <= 0.1 * base - 1:\n",
    "            y_distr[base] += 1\n",
    "            break\n",
    "    if y[-1] > 3.9:\n",
    "        y_distr[-1] += 1\n",
    "print(y_distr)\n",
    "\n",
    "sumy = 0\n",
    "for yi in y_distr:\n",
    "    sumy += yi\n",
    "print(sumy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/root/gru/load_data.py:20: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  source_df['u'] = np.cos(np.radians(source_df['NacWdDir1'])) * source_df['NacWdSpdFltS']\n",
      "/root/gru/load_data.py:21: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  source_df['v'] = np.sin(np.radians(source_df['NacWdDir1'])) * source_df['NacWdSpdFltS']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1565, 9294, 14026, 113246, 438962, 26314, 892, 322, 179]\n",
      "604800\n"
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "scaler = MinMaxScaler()\n",
    "input_size, df = loadradar()\n",
    "df['RadWdSpd1'] -= df['NacWdSpdFltS']\n",
    "rdf = scaler.fit_transform(df)\n",
    "y_distr = [0 for _ in range(10)]\n",
    "for i in range(len(rdf)):\n",
    "    y = rdf[i]\n",
    "    for base in range(1, 10):\n",
    "        if y[-1] <= 0.1 * base:\n",
    "            y_distr[base] += 1\n",
    "            break\n",
    "    if y[-1] > 0.9:\n",
    "        y_distr[-1] += 1\n",
    "print(y_distr)\n",
    "\n",
    "sumy = 0\n",
    "for yi in y_distr:\n",
    "    sumy += yi\n",
    "print(sumy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = ['low', '0.5-0.6', '0.6-0.7', 'high']\n",
    "low = y_distr[0] + y_distr[1] + y_distr[2] + y_distr[3] + y_distr[4]\n",
    "high = y_distr[7] + y_distr[8] + y_distr[9]\n",
    "ys = [low, y_distr[5], y_distr[6], high]\n",
    "# 创建饼图\n",
    "fig1, ax1 = plt.subplots()\n",
    "ax1.pie(ys, labels=labels, autopct='%1.1f%%', shadow=True, startangle=90)\n",
    "ax1.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "\n",
    "# 显示图形\n",
    "plt.show()"
   ]
  }
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